Let me begin by telling you a popular interesting story.
A high school girl went into a retail shop to buy certain things. A few days after, the retail store sent the girl a mail containing coupons for baby clothes and cribs. The girl’s father found this email and was very angry at the retail store for sending his daughter things meant for a pregnant woman.
Shortly afterwards, the man stormed into the retail shop demanding to see the manager. “My daughter got this in the mail!” the father said, “she’s still in high school, and you are already sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?” The manager of the retail store was confused. He looked at the mailer and saw that the man’s claim was true. The mail contained maternity clothing, baby things embedded with pictures of smiling babies. The manager apologized to the angry father.
A few days later, the retail store manager called the father to apologize again but he was stunned at his response. “I had a talk with my daughter,” the father said, “it turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.” The father felt ashamed to admit that he had been wrong.
How did the retail store know that a girl was pregnant even before her father knew? That is the work of Analytics.
(The story above is culled from the article “How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did”)
According to the survey carried out by Bloomberg Businessweek Research Services, about 97% of respondents reported that their companies have adopted analytics to improve their businesses (Clouditate). McKinsey Global Institute 2011 report forecasted that the European government administrators could save over $149 billion in operation efficiency improvements by leveraging data, further estimating that Big Data to generate a 60% increase in retailers’ operating margins on a global scale (Enterpreneur).
According to IDS Systems, Data analytics takes data collected by businesses, categorizes the data, and then indentifies and analyses behavioral information and patterns while Predictive analytics is a branch of data analytics that uses current and historical data to make predictions about future behaviors and events. In general, businesses then use the insights from this analysis to improve productivity and business gain.
Let’s see how Data Analytics can be used to improve your business
The advertising and marketing industry still remains one of the largest and fastest growing industry, with a market value of $1.2 Trillion (Towersofzeyron). Both small and large companies use advertisements to increase their market shares. In fact, there’s virtually no company or brand that can survive without proper allocation of their advertisement budgets.
It was reported that CocaCola spent $3.3 billion on advertising globally in 2013 (Adage). According to the MediaFacts report, a Lagos-based media agency, it was reported that “Nigeria’s total advertising expenditure reached #97.9 billion in 2015 (Financial Nigeria). In 2016, South Africa TV advertising consumes to $1.2 billion. Mobile internet ad revenue in Nigeria in 2017 was estimated to be $27 million (Statista).
According to the US Small Business Administration, as a company it is recommended to spend “7 to 8 percent of your gross revenue for marketing and advertising if you’re doing less than $5 million a year in sales and your net profit margin – after all expenses – is in the 10 percent to 12 percent range” (Small Business).
But how do you know determine the impact of your advertising budget? How do you know you are channeling your resources to the right places?
Imagine a shoe store spending on billboards advertisement in a town where no one wears shoes.
It takes knowledge to know that to have energy, you need to eat food; it takes wisdom to know that you have to put the food in your mouth and not nose.
In the story of a pregnant girl above, Target Corp used Data Analytics to figure out that the girl was pregnant.
Target Corp assigns each customer a peculiar ID number that is tied to their credit card. This ID number reveals their name, email address that stores a history of everything they have bought including their demographic information. Looking at such information, Statisticians at Target Corp analysed the data and discovered a trend or pattern in the customer’s buying. One of the pattern is that “women on the baby registry were buying larger quantities of unscented lotion around the beginning of the second trimester”. They further discovered that pregnant women buy supplements rich in calcium, magnesium and zinc mostly in the first 20 weeks of the pregnancy. More so, the analysts discovered that “many shoppers purchase soap and cotton balls. But when someone suddenly starts buying lots of scent-free soap and extra-big bags of cotton balls, in addition to hand sanitizers and washcloths, it signals they could be getting close to their delivery date.” This analysis enabled the company to make pregnancy prediction. So Target sends coupons for baby items to customers according to their pregnancy scores (Forbes).
Using Data Analytics can help your business know the right customers or right places where to direct your advertising resources. Knowing the right customers to send coupons and discounts will improve the sales of your company.
Business offers a lot of products. You can imagine the number of products Amazon is selling daily. How easy it is for Amazon or Jumia or Konga to make sure that anytime you browse through the store, they recommend products that you will likely purchase for you. That’s the work of Data Analytics.
In the 2018 research work on “E-Commerce Personalization in Africa” carried out by Makuochi Nkwo and other researchers, Jumia and Konga’s e-commerce sites were analysed based on the “requirements regarding customer behavior, in order to find out how they were used to meet customer’s needs, boost loyalty, drive sales and increase conversion”.
The authors revealed that going through Jumia and Konga sites, it was discovered that the sites track and collect information about the browsing pattern of users and uses such information to modify what products are served to the users. The sites analysed user’s previous browsing behaviours and recommend products that they predict the users might want.
The authors then gave an instance that when a user buys wristwatch on the sites, on coming to the sites again, “the system shows the users many other personalized ads of wristwatches offered at discount, especially those that are related to the one that the users checked out during their last visit to the E-commerce site”.
More so, based on the gender and period of time, Jumia and Konga show users some personalized ads. For instance, “on some weekends, Jumia would use personal data that users supplied to determine prospective ready-for-marriage users and forward personalized wedding brand ads or promote/recommend some other items that it feels such category of users might like”.
In this case, the machine analysed the user’s data based on their behaviours when browsing the sites and uses a recommender system to predict what the users might want to buy.
If your company runs an online store, a movie website like Netflix, this is another great way your business might benefit from Data Analytics.
Customers’ Care and Satisfaction
In the article written by Gordon Tredgold on Inc, he shared a story of an e-commerce floral company. Michael Chaplin, The CEO of From You Flowers, hired in-house Ivy League graduates as data analysts. These analysts collected all the historical data of the company for the past ten years between 2002 and 2011, the period in which the company only grew by 10% every year. But after hiring the data analysts in 2011, the company witnessed an increase by 30% between 2011 and 2016.
What did these analysts do differently?
When customers demand for products, the Data Analytics predict their ability to meet the demands from customers, which are often for same day delivery. They use analytics to understand the impact of traffic patterns for each major cities where they are to supply flowers and also the average time it takes to deliver the flowers. This allows the company to meet customers’ demands, and whenever they predict that delivery of products cannot be met perhaps due to time, they either pass on the deal or propose another day for delivery.
This improves the customer’s experience with the company a great deal. There is hardly any rejected products due to late delivery and the company knows the places where its delivery will be timely.
Improving customer’s satisfaction by deploying Data Analytics tools is another great way any brand can enhance its reputation.
Prevention of Bottlenecks
The Michigan State University reported that shipping companies often have logistic challenges of delivering millions of packages each day. Shipping companies usually rely on the performance and reliability of their vehicles which sometimes come short of their reliability.
To mitigate this challenge, shipping companies now use sensor which is attached to each vehicle and is made to store the data of the vehicles during shipping. This data records the condition of every part of the vehicle and by analyzing the data stored by the sensor, Data Analyst could easily tell which part of the vehicle is likely to break down during another shipping. This helps shipping companies tackle the problems beforehand and improve the flow of their business, reduce vehicle downtime while improving customers satisfaction.
More so, whenever a vehicle becomes faulty, the data stored by the sensor can be analysed to determine the cause of the problem, why the problem occur, the likelihood of recurrence and how to prevent future occurrence.
Intelligent Company Expansion
Data analytics can help increase the efficiency of business processes as well as identification of business opportunities such as new locations or areas of expansion where competitors might not have paid attention to. Through data collection, companies get know to the response of their customers based on their geographical demographics. These responses might vary from one geographical location to another.
Using the data collected from your customers based on their locations, delivery process, customers satisfaction, customers demand, variation in product sales, you can predict which location demand more than others and then this analytics can help you determine a location where it is wise to open another shop while reducing the financial risk associated with such task.
Data analytics has a lot to offer both small and large businesses. It reduces bottlenecks in business operations, facilitate customer’s satisfaction, make recommendations that convert leads, and give the company an insight for future business expansion.
Is Data Analytics not great? Why not use its power to boost your business today?